Deep convolutional neural networks for double compressed AMR audio detection

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dc.authorid0000-0002-6404-1499en_US
dc.authorid0000-0002-9174-0367en_US
dc.authorscopusid57215422993en_US
dc.authorscopusid35781455400en_US
dc.contributor.authorBüker, Aykut
dc.contributor.authorHanilçi, Cemal
dc.date.accessioned2022-04-05T06:59:00Z
dc.date.available2022-04-05T06:59:00Z
dc.date.issued2021en_US
dc.departmentBTÜ, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.description.abstractDetection of double compressed (DC) adaptive multi-rate (AMR) audio recordings is a challenging audio forensic problem and has received great attention in recent years. Here, the authors propose to use convolutional neural networks (CNN) for DC AMR audio detection. The CNN is used as (i) an end-to-end DC AMR audio detection system and (ii) a feature extractor. The end-to-end system receives the audio spectrogram as the input and returns the decision whether the input audio is single compressed (SC) or DC. As a feature extractor in turn, it is used to extract discriminative features and then these features are modelled using support vector machines (SVM) classifier. Our extensive analysis conducted on four different datasets shows the success of the proposed system and provides new findings related to the problem. Firstly, double compression has a considerable impact on the high frequency components of the signal. Secondly, the proposed system yields great performance independent of the recording device or environment. Thirdly, when previously altered files are used in the experiments, 97.41% detection rate is obtained with the CNN system. Finally, the cross-dataset evaluation experiments show that the proposed system is very effective in case of a mismatch between training and test datasets.en_US
dc.identifier.doi10.1049/sil2.12028en_US
dc.identifier.endpage280en_US
dc.identifier.issn17519675
dc.identifier.issue4en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage265en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12885/1870
dc.identifier.volume15en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorBüker, Aykut
dc.institutionauthorHanilçi, Cemal
dc.language.isoenen_US
dc.publisherJohn Wiley and Sons Incen_US
dc.relation.ispartofIET Signal Processingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titleDeep convolutional neural networks for double compressed AMR audio detectionen_US
dc.typeArticleen_US

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